|Marian: Fast neural machine translation in C++|
M Junczys-Dowmunt, R Grundkiewicz, T Dwojak, H Hoang, K Heafield, ...
arXiv preprint arXiv:1804.00344, 2018
|From research to production and back: Ludicrously fast neural machine translation|
YJ Kim, M Junczys-Dowmunt, H Hassan, AF Aji, K Heafield, ...
Proceedings of the 3rd Workshop on Neural Generation and Translation, 280-288, 2019
|In neural machine translation, what does transfer learning transfer?|
AF Aji, N Bogoychev, K Heafield, R Sennrich
Association for Computational Linguistics, 2020
|Edinburgh SLT and MT System Description for the IWSLT 2014 Evaluation|
A Birch, M Huck, N Durrani, N Bogoychev, P Koehn
Proceedings of the 10th International Workshop on Spoken Language …, 2014
|Domain, translationese and noise in synthetic data for neural machine translation|
N Bogoychev, R Sennrich
arXiv preprint arXiv:1911.03362, 2019
|The University of Edinburgh's Submissions to the WMT19 News Translation Task|
R Bawden, N Bogoychev, U Germann, R Grundkiewicz, F Kirefu, ...
arXiv preprint arXiv:1907.05854, 2019
|Accelerating asynchronous stochastic gradient descent for neural machine translation|
N Bogoychev, M Junczys-Dowmunt, K Heafield, AF Aji
arXiv preprint arXiv:1808.08859, 2018
|The edinburgh/jhu phrase-based machine translation systems for wmt 2015|
B Haddow, M Huck, A Birch, N Bogoychev, P Koehn
Proceedings of the Tenth Workshop on Statistical Machine Translation, 126-133, 2015
|The University of Edinburgh’s submissions to the WMT18 news translation Task|
B Haddow, N Bogoychev, D Emelin, U Germann, R Grundkiewicz, ...
Proceedings of the Third Conference on Machine Translation: Shared Task …, 2018
|Edinburgh’s submissions to the 2020 machine translation efficiency task|
N Bogoychev, R Grundkiewicz, AF Aji, M Behnke, K Heafield, S Kashyap, ...
Proceedings of the Fourth Workshop on Neural Generation and Translation, 218-224, 2020
|Similar minds post alike: Assessment of suicide risk using a hybrid model|
L Chen, A Aldayel, N Bogoychev, T Gong
Proceedings of the sixth workshop on computational linguistics and clinical …, 2019
|Parallel sentence mining by constrained decoding|
P Chen, N Bogoychev, K Heafield, F Kirefu
Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020
|The University of Edinburgh’s English-German and English-Hausa submissions to the WMT21 news translation task|
P Chen, J Helcl, U Germann, L Burchell, N Bogoychev, AV Miceli-Barone, ...
Proceedings of the Sixth Conference on Machine Translation, 104-109, 2021
|Speed-optimized, compact student models that distill knowledge from a larger teacher model: the uedin-cuni submission to the wmt 2020 news translation task|
U Germann, R Grundkiewicz, M Popel, R Dobreva, N Bogoychev, ...
Proceedings of the Fifth Conference on Machine Translation, 191-196, 2020
|Fast, scalable phrase-based smt decoding|
H Hoang, N Bogoychev, L Schwartz, M Junczys-Dowmunt
arXiv preprint arXiv:1610.04265, 2016
|N-gram language models for massively parallel devices|
N Bogoychev, A Lopez
Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016
|Fast and highly parallelizable phrase table for statistical machine translation|
N Bogoychev, H Hoang
Proceedings of the First Conference on Machine Translation: Volume 1 …, 2016
|Modern MT: A new open-source machine translation platform for the translation industry|
U Germann, E Barbu, M Bentivoglio, N Bogoychev, C Buck, D Caroselli, ...
Baltic Journal of Modern Computing 4 (2), 397-397, 2016
|Efficient machine translation with model pruning and quantization|
M Behnke, N Bogoychev, AF Aji, K Heafield, G Nail, Q Zhu, S Tchistiakova, ...
Proceedings of the Sixth Conference on Machine Translation, 775-780, 2021
|Not all parameters are born equal: Attention is mostly what you need|
arXiv preprint arXiv:2010.11859, 2020